To analyze the correlation between image synthesis quality, image field of view (FoV), and stereo baselines, a dataset consists of various combinations of image FoV and baselines is required. Since there is no such benchmark dataset available, we construct our own dataset by rendering 3D meshes from a real-world dataset Stanford2D3D [1]}. In our dataset, images are organized as two parts, equirectangular projection (ERP) and perspective.
For each 3D mesh, we first generate the ERP dataset using Blender [2]} to render panoramic image sequence at virtual camera viewpoints sampled from a customized path. At each viewpoint, we render RGB-D ERP images with cameras placed along the vertical axis with baseline displacements of \(b\in \lbrace 0m, 0.01m, 0.02m, 0.04m, 0.08m, 0.16m, 0.32m, 0.64m\rbrace \) . An illustration of scene rendering is shown in Figure REF .
